clean up code + prompt engineering for image generation

3d-generation-pipeline/.env.example

@@ -1,8 +1,5 @@
-PIPELINE_FOLDER=
-REFINE_PROMPT=0
+3D_GENERATION_URL=
+MODEL_FOLDER=
 
 CLOUDFLARE_ACCOUNT_ID=
 CLOUDFLARE_API_TOKEN=
-
-3D_GENERATION_URL=
-MODEL_FOLDER=

3d-generation-pipeline/start_pipeline.py

@@ -1,4 +1,3 @@
-import os
 import argparse
 import asyncio
 import logging
@@ -8,14 +7,11 @@ from pathlib import Path
 from datetime import datetime
 from dotenv import load_dotenv
 
-from cloudflare_api import text_to_image_cloudflare, refine_text_prompt
 from generate_image_local import text_to_image_invoke_ai
-from generate_model_local import image_to_3d_api, image_to_3d_subprocess
+from generate_model_local import image_to_3d_api
 
 load_dotenv()
 
-PIPELINE_FOLDER = os.environ["PIPELINE_FOLDER"]
-
 
 def get_timestamp():
     return datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
@@ -26,7 +22,6 @@ def setup_logger(base_folder, timestamp):
     logging.basicConfig(
         filename=log_dir / f"{timestamp}.log",
         level=logging.INFO,
-        #format='%(asctime)s - %(message)s'
         force=True
     )
 
@@ -38,15 +33,9 @@ async def main():
 
     input_prompt = args.prompt
     print(f"Input prompt: {input_prompt}")
+    image_generation_prompt = input_prompt + ", single object, plain neutral background, high-resolution, sharp details, soft studio lighting, front and side visible, realistic style, true-to-scale"
     
-    refine_prompt = os.environ["REFINE_PROMPT"] == "1"
-    if refine_prompt:
-        image_generation_prompt = refine_text_prompt(input_prompt)
-        print(f"Refined prompt: {image_generation_prompt}")
-    else:
-        image_generation_prompt = input_prompt
-    
-    pipeline_folder = Path(PIPELINE_FOLDER)
+    pipeline_folder = Path(__file__).resolve().parent
     timestamp = get_timestamp()
     setup_logger(pipeline_folder, timestamp)
     time_checkpoint = time.time()